796 resultados para Pocahontas, -1617.
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Kirj. O.A. Hainari ja Kustavi Grotenfelt.
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Mode of access: Internet.
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Mode of access: Internet.
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Mode of access: Internet.
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Mode of access: Internet.
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Mode of access: Internet.
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Mode of access: Internet.
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Thesis (doctoral)--Universitat Gteifswald.
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Portions of the work appeared originally in Macmillan's magazine as "Sunderland and Sacharissa," "Sacharissa's letters," and "The Savile papers."
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Audit report on Pocahontas County, Iowa for the year ended June 30, 2015
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We test the broken windows theory using a field experiment in a shared area of an academic workplace(the department common room). More specifically, we explore academics’ and postgraduate students’ behavior under an order condition (a clean environment) and a disorder condition (a messy environment). We find strong evidence that signs of disorderly behavior trigger littering: In 59% of the cases, subjects litter in the disorder treatment as compared to 18% in the order condition. These results remain robust in a multivariate analysis even when controlling for a large set of factors not directly examined by previous studies. Overall, when academic staff and postgraduate students observe that others have violated the social norm of keeping the common room clean, all else being equal, the probability of littering increases by around 40%.
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In this paper, we report the development of novel Pt/nanostructured RuO2/SiC Schottky diode based sensors for hydrogen gas applications. The nanostructured ruthenium oxide thin films were deposited on SiC substrates using radio frequency sputtering technique. Scanning electron microscopy revealed the sputtered RuO2 layer consists of nano-cubular structures with dimensions ranging between 10 and 50 nm. X-ray diffraction confirmed the presence of tetragonal ruthenium (IV) oxide, with preferred orientation along the (101) lattice plane. The current-voltage characteristics of the sensors were investigated towards hydrogen gas in synthetic air at different temperatures from 25 °C to 240 °C. The dynamic responses of the sensors were studied at an optimum temperature of 240 °C and a voltage shift of 304 mV was recorded toward 1% hydrogen gas.
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Mortality and cost outcomes of elderly intensive care unit (ICU) trauma patients were characterised in a retrospective cohort study from an Australian tertiary ICU. Trauma patients admitted between January 2000 and December 2005 were grouped into three major age categories: aged ≥65 years admitted into ICU (n=272); aged ≥65 years admitted into general ward (n=610) and aged <65 years admitted into ICU (n=1617). Hospital mortality predictors were characterised as odds ratios (OR) using logistic regression. The impact of predictor variables on (log) total hospital-stay costs was determined using least squares regression. An alternate treatment-effects regression model estimated the mortality cost-effect as an endogenous variable. Mortality predictors (P ≤0.0001, comparator: ICU ≥65 years, ventilated) were: ICU <65 not-ventilated (OR 0.014); ICU <65 ventilated (OR 0.090); ICU age ≥65 not-ventilated (OR 0.061) and ward ≥65 (OR 0.086); increasing injury severity score and increased Charlson comorbidity index of 1 and 2, compared with zero (OR 2.21 [1.40 to 3.48] and OR 2.57 [1.45 to 4.55]). The raw mean daily ICU and hospital costs in A$ 2005 (US$) for age <65 and ≥65 to ICU, and ≥65 to the ward were; for year 2000: ICU, $2717 (1462) and $2777 (1494); hospital, $1837 (988) and $1590 (855); ward $933 (502); for year 2005: ICU, $3202 (2393) and $3086 (2307); hospital, $1938 (1449) and $1914 (1431); ward $1180 (882). Cost increments were predicted by age ≥65 and ICU admission, increasing injury severity score, mechanical ventilation, Charlson comorbidity index increments and hospital survival. Mortalitycost-effect was estimated at -63% by least squares regression and -82% by treatment-effects regression model. Patient demographic factors, injury severity and its consequences predict both cost and survival in trauma. The cost mortality effect was biased upwards by conventional least squares regression estimation.